https://github.com/microsoft/lamar-benchmark
공식 코드LaMAR: Benchmarking Localization and Mapping for Augmented Reality
Papers with Code 아카이브
Benchmarking
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/microsoft/private-benchmarking
공식 코드TRUCE: Private Benchmarking to Prevent Contamination and Improve Comparative Evaluation of LLMs
https://github.com/microsoft/probts
공식 코드ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons
https://github.com/microsoft/subseasonal_data
공식 코드SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking
https://github.com/microsoft/subseasonal_toolkit
공식 코드SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking
https://github.com/microsoft/syntheseus
공식 코드https://github.com/mihaioltean/evolve-algorithms
공식 코드https://github.com/mikelasz/benchmarking-fairness-imageupsampling
공식 코드https://github.com/mikelma/craftium
공식 코드Craftium: An Extensible Framework for Creating Reinforcement Learning Environments
https://github.com/mikewangwzhl/eeg-to-text
공식 코드https://github.com/mikivishy/fullfront
공식 코드FullFront: Benchmarking MLLMs Across the Full Front-End Engineering Workflow
https://github.com/mikudehuane/FedLaAvg
공식 코드Distributed Non-Convex Optimization with Sublinear Speedup under Intermittent Client Availability
https://github.com/mila-iqia/milabench
공식 코드https://github.com/mineanybuild/mineanybuild
공식 코드MineAnyBuild: Benchmarking Spatial Planning for Open-world AI Agents
https://github.com/minerllabs/basalt-benchmark
공식 코드https://github.com/minghehe-nobug/svip
공식 코드Benchmarking Multimodal CoT Reward Model Stepwise by Visual Program
https://github.com/mingsun-tse/awesome-pruning-at-initialization
공식 코드https://github.com/mingsun-tse/smile-pruning
공식 코드https://github.com/minjiyoon/cgt
공식 코드Graph Generative Model for Benchmarking Graph Neural Networks
https://github.com/minnesotanlp/cobbler
공식 코드Benchmarking Cognitive Biases in Large Language Models as Evaluators
https://github.com/minqi/wordcraft
공식 코드WordCraft: An Environment for Benchmarking Commonsense Agents
https://github.com/misahub2023/benchmarking-codes-of-the-wcebleedgen-dataset
공식 코드https://github.com/misahub2023/capsule-vision-2024-challenge
공식 코드Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy
https://github.com/mismayil/crow
공식 코드CRoW: Benchmarking Commonsense Reasoning in Real-World Tasks
https://github.com/mit-wu-lab/IntersectionZoo
공식 코드IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
https://github.com/mitibmxgraph/revtrack
공식 코드https://github.com/mitmedialab/medical_hallucination
공식 코드Medical Hallucinations in Foundation Models and Their Impact on Healthcare
https://github.com/mitvis/abstraction-alignment
공식 코드Abstraction Alignment: Comparing Model-Learned and Human-Encoded Conceptual Relationships
https://github.com/mkallipo/affiliation-matching
공식 코드https://github.com/mkartik/Shallow-UWnet
공식 코드Shallow-UWnet : Compressed Model for Underwater Image Enhancement
https://github.com/ml-energy/leaderboard
공식 코드The ML.ENERGY Benchmark: Toward Automated Inference Energy Measurement and Optimization
https://github.com/mlai-yonsei/exceptionalbenchmark
공식 코드Benchmarking Foundation Models on Exceptional Cases: Dataset Creation and Validation
https://github.com/mlcommons/algorithmic-efficiency
공식 코드https://github.com/mlcommons/ck
공식 코드https://github.com/mlcommons/cm4mlops
공식 코드https://github.com/mlcommons/medical
공식 코드MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.